Senior researcher and professor/associate professor in machine learning for medical genetics
Oslo universitetssykehus
- Oslo
- Fast
- Fulltid
Diagnostic routines based on Next Generation DNA sequencing (NGS) are developing fast but are challenged by the deluge in data. There is a need to understand how predictive tools and prioritization algorithms can be effectively incorporated into data analysis work flows. Nowadays genetic diagnostic tests in patients with monogenic disorders use NGS-technologies for whole exome/genome sequencing (WES/WGS). These tests result in a molecular diagnosis in
50% of the patients, yielding a large number of variants of unknown significance underlining the strong need to improve the diagnostic offer for these patients.Medical genetics is an exciting field experiencing a vivid scientific development, with implementation of new, groundbreaking technologies for exploring the patients' genes as a basis for personalized medicine, also known as precision medicine. Department of Medical Genetics plays a central part in the Norwegian health care system. During the COVID pandemic we sequenced 80.000 covid genomes. Yearly, we generate around 5000 whole genome sequences as part of diagnosing patients with a wide array of hereditary diseases.We want a motivated researcher across the field of machine learning and neighboring disciplines (data science, statistics, computational biology) to complement the Department's research activities. An especially important task will be to facilitate integration of Artificial intelligence (AI) predictions with more clinical research applications, utilize and develop novel AI-based prediction tools for variant interpretation outside the known morbid genes and in ncDNA, and implement diagnostic pipelines to improve our locally produced advanced decision support software (ELLA, ). The holder of the position will also play an important part in strengthening the interdisciplinary collaboration with other groups and sections at the Department (group of digital solutions for medical genetics and Section for Laboratory Diagnostics.Key informationApplication deadline:05.05.2024Employer:Oslo universitetssykehus HFTown/city:OsloTitle:Senior researcher and professor/associate professor in machine learning for medical geneticsPositions:1Full-time/part-time:Full-timeEmployment type:RegularPercentage of full-time:100Webcruiter ID:4711533829Social sharing :Work tasks:
- Conduct own research, either in the own research group or as part of one of the existing research groups in the department and at OCBE.
- Lead the process of developing innovative methodology and research strategy for AI based prediction of functional consequences of genetic variation.
- Establish and validate AI-based prediction tools for WGS data analysis.
- Design AI-based analyses of available WGS data protein coding genes and ncDNA, aiming to identify the etiology of their diseases to extend the diagnostic offer to future patients with neurodegenerative and other diseases.
- Contribute to an innovative and interdisciplinary research environment
- Strengthen collaboration between research groups within the Department and the Division ad between these and OCBE
- Obtain external funding for research
- Actively work for outreach networking, in- and outside of Norway
- Scientific qualifications at PhD level or higher in machine learning, or in data science, statistics or mathematics with documented competence in machine learning.
- Scientific interests and experience in medical genetics, molecular biology, computational biology and/or precision medicine.
- Excellent skills in computer programming.
- High professional and strategic research ambitions.
- Personal aptitude.
- Good communication skills in written and oral English is a prerequisite for performing all tasks associated with the position. Applicants who are not competent in Norwegian, Swedish or Danish must acquire such competence within two/three years subsequent to their appointment.
- Salary by agreement.
- Scientific and personal development.
- Flexible working hours, except for standard core time.
- New and constantly updated technological park and evolving technologies.
- An employer participating in the Agreement on Inclusive Working Conditions.
- Annual paid leave for 5 weeks, plus public holidays.
- A unique department with multiple opportunities to develop research themes at the forefront of modern science.
- A friendly professional and stimulating international working environment.
- Access to a network of top-level national and international collaborators.
- A reliable and generous pension agreement
- Good welfare schemes.
- Full access to public health services through membership of the National Insurance Scheme
- Oslo`s family friendly environment with its rich opportunities for culture and outdoor activities.
Applications for the academic part-time position must include:
- Cover letter and CV.
- Complete list of publications.
- Separate list of 10 most relevant publications to be evaluated specifically for the position, with internet links.
- Overview of experience in supervising PhD candidates, including names of the candidates, period of supervision, information on institutions and dates for the presentation of the theses, as well as specific information regarding experience as main- or co-supervisor for each candidate,
- Description of qualifications regarding administration, leadership, teaching and foreign language skills.
- Other relevant qualifications.
- Please scan and send the documents as PDF-files (maximum 2 MB / file).
- See guidelines for designing the application, information for applicants, rules for appointments to Associate/Adjunct Professorships as well as rules concerning pedagogical skills: